Fixture layout optimization of sheet metals by integrating topology optimization into genetic algorithm

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dc.contributor.authorShah Abdul Haseeb
dc.date.accessioned2025-11-13T15:54:30Z
dc.date.available2025-11-13T15:54:30Z
dc.date.issued2022
dc.description.abstractManufacturing process accuracy is highly dependent on how well a workpiece is constrained in fixture. Workpiece is constrained by proper arrangement of fixture elements known as fixture layout. Fixture is comprised of locators and clamps. Fixtures restrain workpiece in such a way that the deformation is minimized during manufacturing process. Most of research is done considering rigid body. The research work on sheet metal is limited and many researchers are focusing on sheet metal due to many applications. A N-3-2-1 method is used for sheet metals which requires (N+3) fixture elements to constrain deformation normal to surface. Genetic Algorithm (GA) is used for fixture layout optimization but it requires high computational effort due to large number of population. A new method for fixture layout optimization is proposed by integrating topology optimization into GA. This method combines GA and topology optimization. In this method, topology optimization reduces population for GA. Objective function of this research is to reduce population for GA and minimize total deformation normal to plane of workpiece while restraining maximum deformation of individual nodes up to 2mm. Proposed approach comprised three stages. In first stage, initial number of clamps are determined. In second stage, population is reduced for GA and feasible area of clamps are identified by using topology optimization technique. In third stage, initial number and position of clamps earlier identified in stage one are optimized using GA. After stage one, two quadrants with highest maximum deformation is taken as design region while other two as non-design region for topology optimization. If clamp region is removed in topology optimization, then that clamp is excluded from workpiece because it indicates that clamp has least effect on deformation. Two case studies flat plate and spacer grid are solved to validate proposed method each case study consists of two subcases in which load applied position and magnitude is varied. Proposed method results 47.5% and 65 % decrease in population for subcase 1 and subcase 2 respectively. However, in subcase 3 and subcase 4 population reduced was 90% and 80% respectively. Convergence criteria is to solve GA for 25% of reduced population. Similarly, total deformation normal to the plane is reduced in each subcase with highest reduction of 86.31% in subcase 1 and lowest of 59.85% in subcase 4. In subcase 1 and subcase 2 optimum results were obtain in 64Th and 46th iteration respectively. Similarly in subcase 3 and subcase 4 optimal results were obtained on 4th and 14th iteration respectively. Results are also compared with previous thesis methods i-e GA and Response Surface Methodology (RSM). Experiment is also performed on case study 1- flat plate to validate results and experimental results are compared with simulation. Experimental results are close to simulation results. This concludes that proposed method is valid and optimal results are found by using less computational effort without compromising performance
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/10091
dc.language.isoen
dc.publisherUMT, Lahore
dc.titleFixture layout optimization of sheet metals by integrating topology optimization into genetic algorithm
dc.typeThesis
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